Cardiovascular disease (CVD) remains the leading cause of illness and death worldwide despite a decrease in the mortality attributable to it in the United State. A more comprehensive understanding of CVD risk profiles leading to more personalized prevention and treatment could lead to reductions in CVD related incidents and deaths. However, CVD risk profiles are complex. Several lines of evidence suggest that CVD is influenced by both environmental exposures and heritable genetic background. Environmental exposures such as poor diet, smoking, personality traits, and psychosocial stress may increase the risks for CVD. Specifically, daily-life stress has attracted tremendous attention over the last few decades due to its association with CVD and intermediary risks. Also, the stress due to pandemic COVID-19 may have additional impact on CVD risks and events. However, we remain far from fully understanding how stress interacts with genes to increase the CVD risks. A more comprehensive understanding of this relationship will provide additional avenues for CVD prevention and treatment. In our prior work we have attempted to identify the interaction between genes and stress leading to increase in CVD risks. Building upon our previous work, we propose to develop a comprehensive understanding of genetic architecture of gene-by-stress interaction on CVD-risk by confirming previously identified and by identifying additional genetic variants that interact with stress to increase the expression of CVD risks. To begin with, we will create a synthetic measurement of stress for the study participants in the UK BioBank. We will use this dataset to strengthen our previously published findings on gene-by-stress interactions with CVD-risks and also to confirm our newly identified pool of genetic variants associated with stress, influencing the CVD-risks.
